Identifying Local Field Potential Biomarkers for Treatment-Resistant Major Depression With Deep Brain Stimulation

Recruiting now · Not applicable

Conditions studied: Major Depressive Disorder, Treatment Resistant Depression

In brief

Major depressive disorder (MDD) is a complex and severe mental illness, characterized by multiple symptoms, and is a leading cause of non-fatal health loss. Despite this, approximately 30% of patients do not respond to standard pharmacological or psychological treatments. Currently, we lack objective brain-based biomarkers to differentiate between natural mood fluctuations and situations requiring intervention. To address this issue, we employed a novel electrophysiology recording device and applied deep brain stimulation (DBS) to 12 MDD patients. Our study aims to use long-term invasive neural signal collection and machine learning techniques to reveal the complex relationship between these signals and depressive symptoms. By applying advanced machine learning algorithms, our goal is to establish highly accurate prediction models to identify biomarkers associated with the occurrence and progression of depression. The research will focus on the spatiotemporal features of neural signals and build personalized depression decoding models based on individual differences through the integration and analysis of large-scale data. By delving into the information contained in neural signals, we hope to contribute to the development of personalized treatment approaches for depression.

Key facts

Study ID
NCT06542094
Run by
West China Hospital
People needed
12
Starts
2024-08-03
Expected to finish
2026-12-03
Last updated by the study team
2024-08-07

Who can join

Age: 18 and older, up to 65. Sex: any. Healthy volunteers: not accepted.

You may qualify if…

You may not qualify if…

Where it is running

Full record on ClinicalTrials.gov

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